ConsumerEdge Exploratory Analysis
Exploratory Data Analysis and Initial Insights
1 Abstract
This report presents an exploratory analysis leveraging three datasets from ConsumerEdge, one of the data providers accessible through the Dewey Data platform. The purpose of this analysis is to demonstrate the kinds of analytical insights that can be derived from the platform’s available datasets and to illustrate the value such data can provide in practical decision-making contexts.
2 ConsumerEdge Example Analysis
Using the ConsumerEdge database that is accessable from the dewey platform, we put together a simple data analysis to show how this data could be used.
We pulled data from 3 seperate tables from with the ConsumerEdge database to study consumer patterns and identify insights gained from evualating the data.
2.1 Year over Year Brand by State
The chart above compares total spend across the five largest brands in this dataset for both 2023 and 2024, segmented by state.
Key Insights:
Walmart (Ex Fuel) consistently holds the highest total spend across all states, with noticeable year-over-year growth in Utah.
Amazon Marketplace shows moderate increases in 2024 spend across states, suggesting sustained online retail demand.
Costco (Ex Fuel) maintains stable spending patterns with only slight variation between states, indicating consistent consumer loyalty.
PayPal and Square reflect lower total spend levels but mirror overall state-level spending behavior, hinting that regional economic differences influence digital payment activity.
2.1.1 Year over Year Trend for Paypal
The following rolling-average plot display the 7-day rolling YoY percent change for Paypal. This chart provide insight into how spending fluctuated seasonally throughout 2024 compared to 2023.
PayPal spending trends showed early-year gains only within Idaho with a steady 5-10% drop for both other states. This may indicate reduced online transactions or a shift towards direct card payments over digital wallet usage.
2.2 Sports Brand Year over Year growth
2.2.1 Filtering to Sports Brands
Next we focus our analysis on four major sports brands: NIKE, ADIDAS, PUMA, and ASICS. 
Key Findings:
- ASICS leads in growth rate at 20.24%, despite being the smallest player - demonstrating successful niche positioning
- PUMA shows strong growth momentum at 19.88%
- NIKE maintains impressive 19.73% growth despite its massive scale - indicating effective expansion strategies
- ADIDAS shows solid growth at 16.65%, though lower than competitors
2.2.2 Industry Growth Momentum
The consistent 16-20% year-over-year growth across all four major sports brands represents a remarkable and telling pattern. This uniform growth trajectory signals a fundamentally healthy and expanding sports apparel industry, rather than mere brand-specific victories.
What This Means:
- Broad Market Expansion: All brands are riding a rising tide, indicating robust consumer demand for sports and athletic wear across price points and market segments
- Sustainable Growth Pattern: The consistent double-digit growth across competitors suggests this is not a temporary surge but a structural shift in consumer behavior toward active lifestyles
- Positive Industry Outlook: With every major player experiencing strong growth simultaneously, the sports apparel market demonstrates exceptional resilience and future potential
2.2.3 Monthly Trend Analysis
The analysis reveals distinct seasonal patterns that are consistent across all years. Let’s examine the monthly spend trends from 2021 to 2025.
Key Seasonal Insights:
October Peak: The highest spending occurs in October across all years, with 2022 reaching $5.3B - driven by multiple converging factors including Back-to-School season culmination and Amazon Prime Big Deal Days
April Surge: Secondary peak in April ($2.0B-$2.5B) suggests spring sports season and summer preparation
Summer Lows: February-March and August-September show the lowest spending periods
Market Decline: Overall spending has decreased from 2022-2023 peaks to 2024-2025, indicating potential market normalization post-pandemic surge
2.3 Spending by Demographic
2.3.1 Average Individual Monthly Spend by Income Level
These two graphs show that average individual monthly spend increases with income level in both subindustries. While the amount spent increases with income, there is a noticeable jump in spending for the highest income group ($150k+), indicating that higher earners tend to spend significantly more on apparel and accessories. Moreover, the Women’s Apparel/Accessories subindustry shows a higher average spend in the highest income level group ($150k+) compared to Men’s Apparel/Accessories.
2.3.2 Average Individual Monthly Transaction Count by Income Level
These visualizations show an interesting trend. While average monthly transaction counts increase with income for Women’s Apparel/Accessories, there is an opposite trend for the Men’s Apparel/Accessories subindustry, where higher income levels correspond to lower transaction counts. This suggests that higher-income individuals may be making fewer but larger purchases in the Men’s Apparel/Accessories subindustry.
Insight: Wealthier consumers may not always make more purchases, but they tend to buy more expensive items in each transaction.
2.3.3 Time Series Decomposition of Spending for 25-34 Age Demographic
This time series decomposition focuses on the 25-34 age demographic from 2023 to 2025. The observed data and trend components are plotted to visualize spending patterns over time. Seasonal decomposition is used to help see the overall trend more clearly without the influence of seasonal fluctuations.
Overall, It shows a relatively stable spending trend from 2023-2025 with a slightly more upward trend beginning from mid-2024. From the observed data, there are clear patterns where spending dips in January and September and peaks around between March and May each year. However, the amplitude of these seasonal fluctuations appear to have increased in 2024 and 2025, suggesting more variability in spending patterns in more recent years.
Insight: Young adult spending shows predictable seasonal patterns but has been more variable in 2024 and 2025.
2.4 Brand Relsilience
Top 20 Most Resilient Brands (Bar Chart): This chart is basically the “Top 20” list that answers the report’s main question: who is most resilient. The key takeaway is that the list is dominated by subscription models (like TRUPANION and NETFLIX), proving that recurring revenue is what creates stability.
Growth Consistency vs. Volatility (Scatter Plot): This scatter plot explains why those brands won. It plots every brand’s ‘growth consistency’ against its ‘volatility.’ The best brands are all in the ideal top-left corner, which means they have high consistency (they grow almost every month) and low volatility (no wild swings).
2.5 Spending per Capita and Largest Brand by State
This map visualizes per capita spending by state, along with the brand that has the highest customer spending in each state. It shows that Nebraska has the highest per capita spending at $402.67 while Michigan has the lowest at $34.87. The map also highlights that Walmart is the top-spending brand in most states, followed by Costco.